Medical AI Search Lab

How is your clinic read by AI?

Search is shifting — from choosing links to asking AI and narrowing down candidates. For a medical practice, appearing in search results is no longer the only thing that matters.

When a patient brings their concerns to an AI, that AI needs the right information to understand your clinic correctly, include it among the options, and keep it in the running as a candidate.

Medical AI Search Lab examines how clinics are surfaced as candidates, how competitors compare, which sources are cited, and how often a clinic survives across a conversation — then turns those findings into concrete improvement tasks, delivered as an improvement brief.

Core Theses

Three premises behind this lab

These are the working premises we share when observing how medical institutions are treated by AI search.

  1. 01

    AI search is shifting from "rankings" toward presenting comparative candidates

    Increasingly, in response to a patient's question, doctors and clinics are surfaced as a shortlist with reasoning — not a single ranked list.

  2. 02

    A single query doesn't reveal the full picture

    AI responses vary with model updates, retrieved sources, query phrasing, and conversational context. One-off questions can mislead.

  3. 03

    The competitors AI surfaces don't necessarily match real-world competitors

    AI may shortlist clinics from a different catchment area or patient segment, resulting in comparative candidates that diverge from on-the-ground competition.

Service Brief

What we deliver

We do not provide website development retainers or general SEO consulting agreements. The deliverables are observational reports and improvement briefs.

  1. Step 01

    Verification report

    We observe how a clinic is recognized, compared, and shortlisted by AI search engines and agents across multiple conditions.

  2. Step 02

    Competitor candidate analysis

    We surface which clinics get presented alongside yours when AI shortlists comparison candidates, and why — including citation source patterns.

  3. Step 03

    Citation source analysis

    We trace which third-party pages AI is drawing from, and where the gaps between current sources and editorial best practice lie.

  4. Step 04

    Improvement brief

    We translate observations into a prioritized list of editorial / structural improvement points — not a vendor lock-in.

  5. Step 05

    Re-verification

    After improvements are applied, we re-run the verification protocol to observe whether the AI-surface signal has shifted.

We do not guarantee display in AI search results, recommendation by AI agents, citation by any specific platform, or improvement of search rankings. Our work centers on observation, structuring, and editorial improvement points.

Articles

Articles are currently available in Japanese only

The article corpus of Medical AI Search Lab is published in Japanese. Service inquiries in English (or Japanese) are welcome. For organizations operating clinics in Japan that serve international patients, we can scope verification protocols that cover queries in multiple languages.

Contact

Discuss how your clinic is surfaced by AI search

Tell us about your situation and what you'd like to verify. We will respond by email and propose a verification scope.

We do not guarantee specific outcomes such as ranking improvement, AI citation, or recommendation by any AI agent.

Email an inquiry

anesthlink@sugaritzinc.com

Operator
株式会社Sugaritz (Medical AI Search Lab 医療機関AI検索ラボ事業)
Representative
代表取締役 佐藤逸郎
Address
〒530-0001 大阪府大阪市北区梅田3丁目2番123号 イノゲート大阪10階
Email
anesthlink@sugaritzinc.com
Supervisor
佐藤逸郎 (麻酔科医)